重离子束辐照诱变啤酒酵母线粒体DNA研究

摘要 II 5. 在不同注量离子束辐照后筛选出来的呼吸缺陷型酵母菌株中扩增获得位 于第 12 染色体上的 SOF1 基因，而在同样的扩增体系中没有得到野生型 菌株的该基因。 6. 选取离子束辐照后筛选出来的呼吸缺陷型酵母菌株再次进行辐照，发现 其在低剂量范围（＜0.93Gy）辐照下非常敏感，而在高剂量范围（＞ 0.93Gy）又表现出一定程度的辐射抗性。 结论： 1. 离子束辐照酵母细胞，直接或间接作用于酵母线粒体DNA，导致线粒体 DNA损伤，形成呼吸缺陷的酵母菌株。 2. I 类内含子和 II 类内含子对于离子束辐照的敏感性不同： II 类内含子比较 稳定，II 类内含子可能利用自身编码的反转录酶通过目的DNA引导的反 转录机制对受到辐照损伤的II 类内含子进行修复。 3. 离子束辐照后 SOF1 基因可能发生了突变，影响酵母细胞的生长。 4. 呼吸缺陷型酵母菌株因其线粒体 DNA发生变化及线粒体功能的改变， 使 呼吸缺陷型酵母菌株在不同剂量区的离子束辐照下表现不同辐射敏感 性。目的： 研究啤酒酵母的线粒体 DNA 在重离子辐照作用下的突变效应及其突变机 理。 材料与方法： 利用兰州重离子研究装置(HIRFL)加速的氖、碳离子辐照酵母细胞，用 TTC 显色培养基筛选呼吸缺陷型酵母菌株，并用 mtDNA 限制性酶切手段分析其突变 规律。采用 PCR扩增并对目的产物测序的方法对辐照后线粒体DNA上的 I 类内 含子和 II类内含子进行研究。 结果： 1. TTC 显色实验表明：离子束辐照导致酵母线粒体上的电子传递链发生改 变，产生的还原氢减少，造成呼吸缺陷。 2. 利用限制性酶切实验对线粒体 DNA进行研究，结果表明：离子束辐照诱 变筛选出来的呼吸缺陷型酵母菌株其线粒体DNA变化明显： 主要表现为 酶切条带缺失严重。即使在同一注量下筛选出来的呼吸缺陷型酵母菌株， 其酶切图谱也不相同。 3. 通过 PCR 手段对辐照后酵母线粒体 DNA 碱基序列进一步进行分析，发 现经不同注量离子束辐照后筛选出来的呼吸缺陷型酵母菌株，其I 类内含 子（ai4 and ai5）经设计不同引物进行扩增，没有获得目的条带，说明此 序列发生了突变，可能对离子束辐照比较敏感。 4. 经不同注量离子束辐照后筛选出来的呼吸缺陷型酵母菌株，其 II 类内含 子（ai2）的碱基序列与野生型相比没有变化，表现出在离子束辐照作用 下比较稳定的特性。

经碳离子束诱变的甜高粱汁酒精发酵高产菌株的研究

为了选育出适合发酵甜高粱汁来生产酒精的酵母菌株，本论文以酒精酵母Saccharomyces cerevisiae YY为材料，利用兰州近代物理研究所重离子研究装置（HIRFL）产生的100MeV/u碳离子束对酒精酵母进行了辐照诱变。采用红四氮唑（TTC）作为筛选指示剂，初筛得到了5株产酒能力有所提高的突变酵母菌。通过甜高粱汁发酵，测定发酵液中酒精含量和残糖，复筛出产酒精能力比出发菌株有明显提高的诱变菌株T4。并对其发酵条件进行了优化，以期获得的结果能够为甜高粱汁工业化生产酒精提供参考数据。通过本论文的研究，得到以下初步结果： 1. 在甜高粱汁培养基中，酒精酵母YY的对数生长期在8-20h之间，此时菌体的生长繁殖比较旺盛，活力最佳，为辐照诱变的最佳时期。辐照后，菌体的存活率随辐照剂量的增加呈现出逐渐衰减的趋势。 2. 红四氮唑TTC是一种无色显色指示剂，活菌中所含的脱氢酶可将它还原成红色，因此可以根据菌落呈色的深浅判断酵母菌产酒精能力的高低，从而挑选出产酒能力较高的菌株。本试验用TTC双层培养基法初步筛选出了利用甜高粱汁发酵生产酒精能力较强的T4酵母菌株。 3. 对影响T4菌发酵甜高粱汁生产酒精的几个主要因素（甜高粱汁糖度、接种量、温度、pH、无机盐）进行了初步探讨研究，得出了T4菌发酵甜高粱汁生产酒精的最适条件为：甜高粱汁糖度22%，接种量10%，温度30oC,pH 4.5 ,无机盐加入量为:（NH4）2SO4 1g/L，KH2PO4 5g/L，MgSO4 3g/L。 4. 对发酵条件进行优化后的中试结果显示：出发菌株YY发酵甜高粱汁的时间为36h，酒精产量为8.6% (V/V) ，而T4突变菌甜高粱汁发酵液中的最终酒精含量可以达到9.8%，发酵时间仅为24h。因此，T4菌在工业应用中很有前景

Direct toxicity assessment of toxic chemicals with electrochemical method

Electrochemical measurement of respiratory chain activity is a rapid and reliable screening for the toxicity on microorganisms. Here, we investigated in-vitro effects of toxin on Escherichia coli (E. coli) that was taken as a model microorganism incubated with ferricyanide. The current signal of ferrocyanide effectively amplified by ultramicroelectrode array (UMEA), which was proven to be directly related to the toxicity. Accordingly, a direct toxicity assessment (DTA) based on chronoamperometry was proposed to detect the effect of toxic chemicals on microorganisms. The electrochemical responses to 3,5-dichlorophenol (DCP) under the incubation times revealed that the toxicity reached a stable level at 60 min, and its 50% inhibiting concentration (IC50) was estimated to be 8.0 mg L-1. At 60 min incubation, the IC50 values for KCN and As2O3 in water samples were 4.9 mg L-1 and 18.3 mg L-1, respectively. But the heavy metal ions, such as Cu2+ Pb2+ and Ni2+, showed no obvious toxicity on E. coli.

Fatty acid biosynthesis in eukaryotic photosynthetic microalgae: Identification of a microsomal delta 12 desaturase in Chlamydomonas reinhardtii

Polyunsaturated fatty acids (PUFAs) are important components of infant and adult nutrition because they serve as structural elements of cell membranes. Fatty acid desaturases are responsible for the insertion of double bonds into pre-formed fatty acid chains in reactions that require oxygen and reducing equivalents. In this study, the genome-wide characterization of the fatty acid desaturases from seven eukaryotic photosynthetic microalgae was undertaken according to the conserved histidine-rich motifs and phylogenetic profiles. Analysis of these genomes provided insight into the origin and evolution of the pathway of fatty acid biosynthesis in eukaryotic plants. In addition, the candidate enzyme from Chlamydomonas reinhardtii with the highest similarity to the microsomal Delta 12 desaturase of Chlorella vulgaris was isolated, and its function was verified by heterologous expression in yeast (Saccharomyces cerevisiae).

Data mining the yeast genome in a lazy functional language

Clare, A. and King R.D. (2003) Data mining the yeast genome in a lazy functional language. In Practical Aspects of Declarative Languages (PADL'03) (won Best/Most Practical Paper award).

Hierarchical Multi-classification with Predictive Clustering Trees in Functional Genomics

Struyf, J., Dzeroski, S. Blockeel, H. and Clare, A. (2005) Hierarchical Multi-classification with Predictive Clustering Trees in Functional Genomics. In proceedings of the EPIA 2005 CMB Workshop

Functional genomic hypothesis generation and experimentation by a robot scientist

King R. D., Whelan, K. E., Jones, F. M., Reiser, P. G. K., Bryant, C. H., Muggleton, S., Kell, D. B. and Oliver, S. G. (2004) Functional genomic hypothesis generation and experimentation by a robot scientist. Nature 427 (6971) p247-252

Detecting separate time scales in genetic expression data.

BACKGROUND: Biological processes occur on a vast range of time scales, and many of them occur concurrently. As a result, system-wide measurements of gene expression have the potential to capture many of these processes simultaneously. The challenge however, is to separate these processes and time scales in the data. In many cases the number of processes and their time scales is unknown. This issue is particularly relevant to developmental biologists, who are interested in processes such as growth, segmentation and differentiation, which can all take place simultaneously, but on different time scales. RESULTS: We introduce a flexible and statistically rigorous method for detecting different time scales in time-series gene expression data, by identifying expression patterns that are temporally shifted between replicate datasets. We apply our approach to a Saccharomyces cerevisiae cell-cycle dataset and an Arabidopsis thaliana root developmental dataset. In both datasets our method successfully detects processes operating on several different time scales. Furthermore we show that many of these time scales can be associated with particular biological functions. CONCLUSIONS: The spatiotemporal modules identified by our method suggest the presence of multiple biological processes, acting at distinct time scales in both the Arabidopsis root and yeast. Using similar large-scale expression datasets, the identification of biological processes acting at multiple time scales in many organisms is now possible.

Conservation, duplication, and loss of the Tor signaling pathway in the fungal kingdom.

BACKGROUND: The nutrient-sensing Tor pathway governs cell growth and is conserved in nearly all eukaryotic organisms from unicellular yeasts to multicellular organisms, including humans. Tor is the target of the immunosuppressive drug rapamycin, which in complex with the prolyl isomerase FKBP12 inhibits Tor functions. Rapamycin is a gold standard drug for organ transplant recipients that was approved by the FDA in 1999 and is finding additional clinical indications as a chemotherapeutic and antiproliferative agent. Capitalizing on the plethora of recently sequenced genomes we have conducted comparative genomic studies to annotate the Tor pathway throughout the fungal kingdom and related unicellular opisthokonts, including Monosiga brevicollis, Salpingoeca rosetta, and Capsaspora owczarzaki. RESULTS: Interestingly, the Tor signaling cascade is absent in three microsporidian species with available genome sequences, the only known instance of a eukaryotic group lacking this conserved pathway. The microsporidia are obligate intracellular pathogens with highly reduced genomes, and we hypothesize that they lost the Tor pathway as they adapted and streamlined their genomes for intracellular growth in a nutrient-rich environment. Two TOR paralogs are present in several fungal species as a result of either a whole genome duplication or independent gene/segmental duplication events. One such event was identified in the amphibian pathogen Batrachochytrium dendrobatidis, a chytrid responsible for worldwide global amphibian declines and extinctions. CONCLUSIONS: The repeated independent duplications of the TOR gene in the fungal kingdom might reflect selective pressure acting upon this kinase that populates two proteinaceous complexes with different cellular roles. These comparative genomic analyses illustrate the evolutionary trajectory of a central nutrient-sensing cascade that enables diverse eukaryotic organisms to respond to their natural environments.

Chromatin: bind at your own RSC.

Recent work has identified a novel RSC-nucleosome complex that both strongly phases flanking nucleosomes and presents regulatory sites for ready access. These results challenge several widely held views.

Measuring fast gene dynamics in single cells with time-lapse luminescence microscopy.

Time-lapse fluorescence microscopy is an important tool for measuring in vivo gene dynamics in single cells. However, fluorescent proteins are limited by slow chromophore maturation times and the cellular autofluorescence or phototoxicity that arises from light excitation. An alternative is luciferase, an enzyme that emits photons and is active upon folding. The photon flux per luciferase is significantly lower than that for fluorescent proteins. Thus time-lapse luminescence microscopy has been successfully used to track gene dynamics only in larger organisms and for slower processes, for which more total photons can be collected in one exposure. Here we tested green, yellow, and red beetle luciferases and optimized substrate conditions for in vivo luminescence. By combining time-lapse luminescence microscopy with a microfluidic device, we tracked the dynamics of cell cycle genes in single yeast with subminute exposure times over many generations. Our method was faster and in cells with much smaller volumes than previous work. Fluorescence of an optimized reporter (Venus) lagged luminescence by 15-20 min, which is consistent with its known rate of chromophore maturation in yeast. Our work demonstrates that luciferases are better than fluorescent proteins at faithfully tracking the underlying gene expression.

Selection of yeast strains for bioethanol production from UK seaweeds

Macroalgae (seaweeds) are a promising feedstock for the production of third generation bioethanol, since they have high carbohydrate contents, contain little or no lignin and are available in abundance. However, seaweeds typically contain a more diverse array of monomeric sugars than are commonly present in feedstocks derived from lignocellulosic material which are currently used for bioethanol production. Hence, identification of a suitable fermentative microorganism that can utilise the principal sugars released from the hydrolysis of macroalgae remains a major objective. The present study used a phenotypic microarray technique to screen 24 different yeast strains for their ability to metabolise individual monosaccharides commonly found in seaweeds, as well as hydrolysates following an acid pre-treatment of five native UK seaweed species (Laminaria digitata, Fucus serratus, Chondrus crispus, Palmaria palmata and Ulva lactuca). Five strains of yeast (three Saccharomyces spp, one Pichia sp and one Candida sp) were selected and subsequently evaluated for bioethanol production during fermentation of the hydrolysates. Four out of the five selected strains converted these monomeric sugars into bioethanol, with the highest ethanol yield (13 g L−1) resulting from a fermentation using C. crispus hydrolysate with Saccharomyces cerevisiae YPS128. This study demonstrated the novel application of a phenotypic microarray technique to screen for yeast capable of metabolising sugars present in seaweed hydrolysates; however, metabolic activity did not always imply fermentative production of ethanol.

Evaluation of predicted network modules in yeast metabolism using NMR-based metabolite profiling

Genome-scale metabolic models promise important insights into cell function. However, the definition of pathways and functional network modules within these models, and in the biochemical literature in general, is often based on intuitive reasoning. Although mathematical methods have been proposed to identify modules, which are defined as groups of reactions with correlated fluxes, there is a need for experimental verification. We show here that multivariate statistical analysis of the NMR-derived intra- and extracellular metabolite profiles of single-gene deletion mutants in specific metabolic pathways in the yeast Saccharomyces cerevisiae identified outliers whose profiles were markedly different from those of the other mutants in their respective pathways. Application of flux coupling analysis to a metabolic model of this yeast showed that the deleted gene in an outlying mutant encoded an enzyme that was not part of the same functional network module as the other enzymes in the pathway. We suggest that metabolomic methods such as this, which do not require any knowledge of how a gene deletion might perturb the metabolic network, provide an empirical method for validating and ultimately refining the predicted network structure.

Comparison of techniques to examine the diversity of fungi in adult patients with cystic fibrosis

This study compares conventional and molecular techniques for the detection of fungi in 77 adult cystic fibrosis (CF) patients. Three different methods were investigated, i.e., (1) conventional microbiological culture (including yeasts and filamentous fungi), (2) mycological culture with CF-derived fungal specific culture media, and (3) Non-culture and direct DNA extraction from patient sputa. Fungi isolated from environmental air samples of the CF unit were compared to fungi in sputa from CF patients. Fungi (n = 107) were detected in 14/77(18%) of patients by method 1, in 60/77 (78%) of patients by method 2 and with method 3, in 77/77(100%) of the patients. The majority of yeasts isolated were Candida albicans and C. dubliniensis. Exophiala (Wangiella) dermatitidis, Scedosporiumapiospermum, Penicillium spp., Aspergillus fumigatus, and Aspergillus versicolor were also identified by sequence analysis of the rDNA short internal transcribed spacer (ITS2) region. Conventional laboratory analysis failed to detect fungi in 63 patients mainly due to overgrowth by Gram-negative organisms. Mycological culture with antibiotics dramatically increased the number of fungi that could be detected. Molecular techniques detected fungi such as Saccharomyces cerevisiae, Malassezia spp., Fuscoporia ferrea, Fusarium culmorum, Acremonium strictum, Thanatephorus cucumeris and Cladosporium spp. which were not found with other methods. This study demonstrates that several potentially important fungi may not be detected if mycological culture methods alone are used. A polyphasic approach employing both enhanced mycological culture with molecular detection will help determine the presence of fungi in the sputa of patients with CF and their healthcare environment.

RNA polymerase I-specific subunits promote polymerase clustering to enhance the rRNA gene transcription cycle.

RNA polymerase I (Pol I) produces large ribosomal RNAs (rRNAs). In this study, we show that the Rpa49 and Rpa34 Pol I subunits, which do not have counterparts in Pol II and Pol III complexes, are functionally conserved using heterospecific complementation of the human and Schizosaccharomyces pombe orthologues in Saccharomyces cerevisiae. Deletion of RPA49 leads to the disappearance of nucleolar structure, but nucleolar assembly can be restored by decreasing ribosomal gene copy number from 190 to 25. Statistical analysis of Miller spreads in the absence of Rpa49 demonstrates a fourfold decrease in Pol I loading rate per gene and decreased contact between adjacent Pol I complexes. Therefore, the Rpa34 and Rpa49 Pol I–specific subunits are essential for nucleolar assembly and for the high polymerase loading rate associated with frequent contact between adjacent enzymes. Together our data suggest that localized rRNA production results in spatially constrained rRNA production, which is instrumental for nucleolar assembly.